Milling Chatter Prediction Based on the Information Entropy and Support Vector Machine

DOI

10.2991/iiicec-15.2015.86How to use a DOI?

Keywords

Milling Chatter Prediction; Multi-scale Permutation Entropy; Wavelet Packet Energy entropy; Support Vector Machine

Abstract

This paper proposes a method based on information entropy and support vector machine to predict chatter in milling, it uses multi-scale permutation entropy and wavelet packet energy entropy as the milling chatter premonition features, we select parameters of these identifying features by experimental analysis, and predict chatter using the SVM which use these two identifying features as its input. The results show that this method can effectively predict the occurrence of milling chatter, correct rate is 95.8%.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bing Chen
AU  - Jie Yang
AU  - Ju Zhao
AU  - Jingbo Ren
PY  - 2015/03
DA  - 2015/03
TI  - Milling Chatter Prediction Based on the Information Entropy and Support Vector Machine
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 376
EP  - 380
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.86
DO  - 10.2991/iiicec-15.2015.86
ID  - Chen2015/03
ER  -